首页> 外军国防科技报告 >ARL-TR-8619 - A Facial Recognition Algorithm Comparison: Using a Hybrid EigenFace ARTMAP Neural Network vs. the Tracking-Learning-Detection (TLD) Algorithm | U.S. Army Research Laboratory
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ARL-TR-8619 - A Facial Recognition Algorithm Comparison: Using a Hybrid EigenFace ARTMAP Neural Network vs. the Tracking-Learning-Detection (TLD) Algorithm | U.S. Army Research Laboratory

机译:ARL-TR-8619 - 面部识别算法比较:使用混合EigenFace ARTMAp神经网络与跟踪学习检测(TLD)算法美国陆军研究实验室

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摘要

This report describes a comparison of two facial recognition processes for continuous learning. One process used an ARTMAP neural network with features extracted using a modified EigenFace implementation. This was compared with training the Tracking-Learning-Detection (TLD) algorithm using faces from a television episode. Results indicated that the TLD algorithm was superior to the Hybrid EigenFace/ARTMAP (EA) for the entire episode but that the Hybrid EA algorithm was better for the second half of the episode. The ARTMAP was chosen because it can adaptively train to new vectors without suffering from catastrophic forgetting. However, the TLD algorithm was capable of better online learning and overall performance.

著录项

  • 作者单位
  • 年(卷),期 2019(),
  • 年度 2019
  • 页码
  • 总页数 17
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 网站名称 美国陆军研究实验室
  • 栏目名称 全部文件
  • 关键词

  • 入库时间 2022-08-19 17:01:46
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